{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f64fd14e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "plt.rcParams['axes.unicode_minus']=False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3a7c33e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>区域</th>\n",
       "      <th>2022年销量</th>\n",
       "      <th>2021年销量</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>华东</td>\n",
       "      <td>1215</td>\n",
       "      <td>1003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>西北</td>\n",
       "      <td>1321</td>\n",
       "      <td>1265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>东北</td>\n",
       "      <td>1426</td>\n",
       "      <td>1531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>华北</td>\n",
       "      <td>1531</td>\n",
       "      <td>1436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>华南</td>\n",
       "      <td>2238</td>\n",
       "      <td>2066</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   区域  2022年销量  2021年销量\n",
       "0  华东     1215     1003\n",
       "1  西北     1321     1265\n",
       "2  东北     1426     1531\n",
       "3  华北     1531     1436\n",
       "4  华南     2238     2066"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.read_excel('第二章 图表(前15).xlsx',sheet_name='6 蝴蝶图',usecols=\"B,D,F\",skiprows=1)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4ff0eac0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "plt.barh(data['区域'], data['2022年销量'], color='skyblue', label='2022年销量')\n",
    "\n",
    "plt.barh(data['区域'], -data['2021年销量'], color='lightcoral', label='2021年销量')\n",
    "\n",
    "for index, value in enumerate(data['2022年销量']):\n",
    "    plt.text(value, index, str(value), va='center', ha='left')\n",
    "for index, value in enumerate(data['2021年销量']):\n",
    "    plt.text(-value, index, str(value), va='center', ha='right')\n",
    "\n",
    "plt.title('2022年上半年各区域对比去年销量')\n",
    "plt.xlabel('销量')\n",
    "plt.ylabel('区域')\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.4"
  }
 },
 "nbformat": 4,
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